Tag: machine learning

Total 81 Posts

Gradient Descent in Python: Implementation and Theory

Introduction

This tutorial is an introduction to a simple optimization technique called gradient descent, which has seen major application in state-of-the-art machine learning models.

We'll develop a general purpose routine to implement gradient descent and apply it to solve different problems, including classification via supervised learning.

In this process, we'll

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Sentiment Analysis in Python With TextBlob

Introduction

State-of-the-art technologies in NLP allow us to analyze natural languages on different layers: from simple segmentation of textual information to more sophisticated methods of sentiment categorizations.

However, it does not inevitably mean that you should be highly advanced in programming to implement high-level tasks such as sentiment analysis in

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Simple NLP in Python With TextBlob: Tokenization

Introduction

The amount of textual data on the Internet has significantly increased in the past decades. There's no doubt that the processing of this amount of information must be automated, and the TextBlob package is one of the fairly simple ways to perform NLP - Natural Language Processing.

It provides

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Kernel Density Estimation in Python Using Scikit-Learn

Introduction

This article is an introduction to kernel density estimation using Python's machine learning library scikit-learn.

Kernel density estimation (KDE) is a non-parametric method for estimating the probability density function of a given random variable. It is also referred to by its traditional name, the Parzen-Rosenblatt Window method, after its

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Deep Learning in Keras - Building a Deep Learning Model

Introduction

Deep learning is one of the most interesting and promising areas of artificial intelligence (AI) and machine learning currently. With great advances in technology and algorithms in recent years, deep learning has opened the door to a new era of AI applications.

In many of these applications, deep learning

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